Articles producció científica> Enginyeria Química

Variation-preserving normalization unveils blind spots in gene expression profiling

  • Identification data

    Identifier: PC:2705
    Authors:
    Roca, C.P.Gomes, S.I.L.Amorim, M.J.B.Scott-Fordsmand, J.J.
    Abstract:
    RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression.
  • Others:

    Author, as appears in the article.: Roca, C.P.; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.
    Department: Enginyeria Química
    URV's Author/s: PEREZ ROCA, CARLOS; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.
    Keywords: gene expression profiling reproducibility Gene expression regulation
    Abstract: RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression.
    Thematic Areas: Enginyeria química Ingeniería química Chemical engineering
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 2045-2322
    Author identifier: ; n/a; n/a; 0000-0002-2260-1224
    Record's date: 2017-03-28
    Journal volume: 7
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.nature.com/articles/srep42460
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1038/srep42460
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2017
    Publication Type: Article Artículo Article
  • Keywords:

    Expressió gènica -- Mètodes estadístics
    Microxips de DNA -- Mètodes estadístics
    gene expression profiling
    reproducibility
    Gene expression regulation
    Enginyeria química
    Ingeniería química
    Chemical engineering
    2045-2322
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